RAQUEL GÓMEZ-MOLINA^1,*, RAQUEL MARTÍNEZ^2,3,4, MIGUEL SUÁREZ^2,3,4,*, ANA PEÑA-CABIA¹, MARíA CONCEPCIóN CALDERÓN¹, JORGE MATEO^3,4

Oncology Research, Vol.33, No.7, pp. 1531-1545, 2025, DOI:10.32604/or.2025.063951 - 26 June 2025

Abstract Lynch syndrome (LS), also known as hereditary non-polyposis colorectal cancer (HNPCC), is an inherited condition associated with a higher risk of colorectal cancer (CRC) and other cancers. It is caused by germline mutations in DNA mismatch repair (MMR) genes, including MLH1, MSH2, MSH6 and PMS2. These mutations lead to microsatellite instability (MSI) and defective DNA repair mechanisms, resulting in increased cancer risk. Early detection of LS is crucial for effective management and cancer prevention. Endoscopic surveillance, particularly regular colonoscopy, is recommended for individuals with LS to detect CRC at early stages. Additionally, universal screening of CRC for More > Graphic Abstract

Ji-Yuan Ding¹, Wang-Su Jeon², Sang-Yong Rhee^2,*, Chang-Man Zou^1,3

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3989-4014, 2024, DOI:10.32604/cmc.2024.057473 - 19 December 2024

Abstract In complex agricultural environments, cucumber disease identification is confronted with challenges like symptom diversity, environmental interference, and poor detection accuracy. This paper presents the DM-YOLO model, which is an enhanced version of the YOLOv8 framework designed to enhance detection accuracy for cucumber diseases. Traditional detection models have a tough time identifying small-scale and overlapping symptoms, especially when critical features are obscured by lighting variations, occlusion, and background noise. The proposed DM-YOLO model combines three innovative modules to enhance detection performance in a collective way. First, the MultiCat module employs a multi-scale feature processing strategy with… More >

Xiaorui Zhang^1,2,3,*, Qijian Xie¹, Wei Sun^3,4, Yongjun Ren^1,2,3, Mithun Mukherjee⁵

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 47-61, 2023, DOI:10.32604/cmc.2023.042561 - 31 October 2023

Abstract Fall behavior is closely related to high mortality in the elderly, so fall detection becomes an important and urgent research area. However, the existing fall detection methods are difficult to be applied in daily life due to a large amount of calculation and poor detection accuracy. To solve the above problems, this paper proposes a dense spatial-temporal graph convolutional network based on lightweight OpenPose. Lightweight OpenPose uses MobileNet as a feature extraction network, and the prediction layer uses bottleneck-asymmetric structure, thus reducing the amount of the network. The bottleneck-asymmetrical structure compresses the number of input… More >

Motasem S. Alsawadi^1,*, El-Sayed M. El-kenawy^2,3, Miguel Rio¹

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 19-36, 2023, DOI:10.32604/cmc.2023.032499 - 22 September 2022

Abstract The ever-growing available visual data (i.e., uploaded videos and pictures by internet users) has attracted the research community's attention in the computer vision field. Therefore, finding efficient solutions to extract knowledge from these sources is imperative. Recently, the BlazePose system has been released for skeleton extraction from images oriented to mobile devices. With this skeleton graph representation in place, a Spatial-Temporal Graph Convolutional Network can be implemented to predict the action. We hypothesize that just by changing the skeleton input data for a different set of joints that offers more information about the action of More >

Xufeng Li^1,2,3, Yantao Bi^1,2,3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.6, pp. 1699-1709, 2022, DOI:10.32604/fdmp.2022.019741 - 27 June 2022

Abstract Using the conservation equations for mass, momentum and energy, a model is elaborated to describe the dynamics of high-energy gases in composite-perforation technological processes. The model includes a precise representation of the gunpowder combustion and related killing fluid displacement. Through numerical solution of such equations, the pressure distribution of the high-energy gas in fractures is obtained, and used to determine crack propagation. The accuracy of the model is verified by comparing the simulation results with actual measurements. More > Graphic Abstract

Adel Hafeezallah¹, Ahlam Al-Dhamari^2,3,*, Syed Abd Rahman Abu-Bakar²

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3879-3903, 2022, DOI:10.32604/cmc.2022.028289 - 16 June 2022

Abstract Estimating the crowd count and density of highly dense scenes witnessed in Muslim gatherings at religious sites in Makkah and Madinah is critical for developing control strategies and organizing such a large gathering. Moreover, since the crowd images in this case can range from low density to high density, detection-based approaches are hard to apply for crowd counting. Recently, deep learning-based regression has become the prominent approach for crowd counting problems, where a density-map is estimated, and its integral is further computed to acquire the final count result. In this paper, we put forward a… More >

Jiabao Shi¹, Zhao Qiu^1,*, Tao Chen¹, Jiale Lin¹, Hancheng Huang², Yunlong He³, Yu Yang³

Journal of New Media, Vol.4, No.2, pp. 97-106, 2022, DOI:10.32604/jnm.2022.027176 - 13 June 2022

Abstract Big data is a comprehensive result of the development of the Internet of Things and information systems. Computer vision requires a lot of data as the basis for research. Because skeleton data can adapt well to dynamic environment and complex background, it is used in action recognition tasks. In recent years, skeleton-based action recognition has received more and more attention in the field of computer vision. Therefore, the keypoints of human skeletons are essential for describing the pose estimation of human and predicting the action recognition of the human. This paper proposes a skeleton point More >

Kuei-Feng Chang¹, Wen-Goang Yang², Ya-Wen Cheng³, I-Tung Shih^2,*

International Journal of Mental Health Promotion, Vol.24, No.2, pp. 219-236, 2022, DOI:10.32604/ijmhp.2022.018187 - 18 January 2022

Abstract This study explored the mechanism on how volunteers as rationalists use rationalism during their cognitive appraisal process when dealing with emotional events in their social helping behavior such as international rescue events. The authors used the triangulation method to include three studies (Study 1 is a qualitative research which explored ways of TCF leader’s inspiring their volunteer workers; Study 2 is a quantitative research on the decision-making process of volunteer individuals involving in international rescue activities; Study 3 is a quantitative research on individuals’ motivation for joining social helping behavior) for validation of Tzu Chi… More >

Peter Pommerville¹, S. Larry Goldenberg², James W.L. Wilson³, Yves Fradet⁴, Jacques Corcos⁵, Brian A.P. Morris⁶

Canadian Journal of Urology, Vol.11, No.3, pp. 2290-2295, 2004

Abstract Introduction: Knowledge of the current status of manpower and resources is important in understanding the state of any medical specialty, and critical in planning for future recruitment, funding and infrastructure development.
Methods: In 2003, the Canadian Urological Association (CUA) conducted two nationwide surveys examining manpower, resources, and the technology available. One survey went only to academic and hospital leaders across the country (the resources survey), while the other was sent to the entire general membership of the CUA.
Results: The response rate for the resources survey was 67%, while that for the membership survey was 50.4%. The respondents'… More >